Craqly VS Txt2SQL

Craqly's answer

Three practical reasons. First, no bot joins your call, so there is no consent popup for the other side and no procurement objection; recorder-bots like Otter or Fireflies add a visible participant. Second, you get help in real time (1-2 seconds) instead of a summary email twenty minutes after the moment has passed. Third, one app covers three jobs: sales calls with battle cards and objection handling, interviews with answers anchored in your resume, and meetings with automatic action items and recap emails. There is a free tier with no credit card, so you can test it on a real call before deciding.

Craqly's answer

Craqly works during the call, not after it. Most meeting AI joins your call as a bot, records everything, and sends a summary once the conversation is over. Craqly listens to system audio directly (no bot joins, nothing appears on the guest list), and surfaces answers, objection counters, and action items in 1-2 seconds while you can still use them. The overlay is excluded from screen capture at the OS level, so when you share your screen the other side sees nothing. It also transcribes 18 languages with natural mid-conversation switching.

Craqly's answer

People whose income depends on how a live conversation goes. Sales professionals in discovery, demo, negotiation and closing calls. Job seekers in behavioral, technical and coding interviews. Recruiters screening candidates. Managers running standups, planning sessions and retros who want action items captured without a notetaker bot in the room. Because the app transcribes 18 languages with mid-conversation switching, a lot of usage comes from bilingual teams that flip between English and a local language in the same meeting.

Craqly's answer

Craqly is built by Fyrosoft Tech in Hyderabad, India. The team started with an interview copilot (LastRound AI) and kept hearing the same complaint from users about every meeting tool: the AI shows up after the call, when the summary can only tell you what you should have said. So we rebuilt the idea around the call itself: streaming transcription, context-aware suggestions in 1-2 seconds, and a desktop overlay that stays out of screen-share. Getting real-time latency low enough to be useful mid-sentence was the hard engineering problem, and it is the reason the product exists as a desktop app rather than another meeting bot.